Comparison of regression estimators using Pitman measures of nearness

Received: August 5, 1999; revised version: June 14, 2000     

Generalized minimum distance estimators of a linear model with correlated errors

R^p of a linear regression model of the type Y = Xθ + ɛ, where X is the design matrix, Y the vector of the response variable and ɛ the random error vector that follows an AR(1) correlation structure. These estimators are asymptotically analyzed, by proving their strong consistency, asymptotic normality and asymptotic efficiency. In a simulation study, a better behaviour of the Mean Squared Error of the proposed estimator with respect to that of the generalized least squares estimators is observed. Received: November 16, 1998; revised version: May 10, 2000     

Generalized least squares with misspecified serial correlation structures

Summary. The regression literature contains hundreds of studies on serially correlated disturbances. Most of these studies assume that the structure of the error covariance matrix Ω is known or can be estimated consistently from data. Surprisingly, few studies investigate the properties of estimated generalized least squares (GLS) procedures when the structure of Ω is incorrectly identified and the parameters are inefficiently estimated. We compare the finite sample efficiencies of ordinary least squares (OLS), GLS and incorrect GLS (IGLS) estimators. We also prove new theorems establishing theoretical efficiency bounds for IGLS relative to GLS and OLS. Results from an exhaustive simulation study are used to evaluate the finite sample performance and to demonstrate the robustness of IGLS estimates vis-à-vis OLS and GLS estimates constructed for models with known and estimated (but correctly identified) Ω. Some of our conclusions for finite samples differ from established asymptotic results.     

Nonparametric estimation of the mean function of a stochastic process with missing observations

In an attempt to identify similarities between methods for estimating a mean function with different types of response or observation processes, we explore a general theoretical framework for nonparametric estimation of the mean function of a response process subject to incomplete observations. Special cases of the response process include quantitative responses and discrete state processes such as survival processes, counting processes and alternating binary processes. The incomplete data are assumed to arise from a general response-independent observation process, which includes right- censoring, interval censoring, periodic observation, and mixtures of these as special cases. We explore two criteria for defining nonparametric estimators, one based on the sample mean of available data and the other inspired by the construction of Kaplan-Meier (or product-limit) estimator [J. Am. Statist. Assoc. 53 (1958) 457] for right-censored survival data. We show that under regularity conditions the estimated mean functions resulting from both criteria are consistent and converge weakly to Gaussian processes, and provide consistent estimators of their covariance functions. We then evaluate these general criteria for specific responses and observation processes, and show how they lead to familiar estimators for some response and observation processes and new estimators for others. We illustrate the latter with data from an recently completed AIDS clinical trial.     

Bootstrap prediction intervals for autoregressive conditional duration models

In the recent past, the autoregressive conditional duration (ACD) models have gained popularity in modelling the durations between successive events. The aim of this paper is to propose a simple and distribution free re-sampling procedure for developing the forecast intervals of linear ACD Models. We use the conditional least squares method to estimate the parameters of the ACD Model instead of the conditional Maximum Likelihood Estimation or Quasi-Maximum Likelihood Estimation and show that they are consistent for large samples. The properties of the proposed procedure are illustrated by a simulation study and an application to two real data sets.     

Distributionally Robust Optimization of Two‐Stage Lot‐Sizing Problems

This paper studies two‐stage lot‐sizing problems with uncertain demand, where lost sales, backlogging and no backlogging are all considered. To handle the ambiguity in the probability distribution of demand, distributionally robust models are established only based on mean‐covariance information about the distribution. Based on shortest path reformulations of lot‐sizing problems, we prove that robust solutions can be obtained by solving mixed 0‐1 conic quadratic programs (CQPs) with mean‐risk objective functions. An exact parametric optimization method is proposed by further reformulating the mixed 0‐1 CQPs as single‐parameter quadratic shortest path problems. Rather than enumerating all potential values of the parameter, which may be the super‐polynomial in the number of decision variables, we propose a branch‐and‐bound‐based interval search method to find the optimal parameter value. Polynomial time algorithms for parametric subproblems with both uncorrelated and partially correlated demand distributions are proposed. Computational results show that the proposed models greatly reduce the system cost variation at the cost of a relative smaller increase in expected system cost, and the proposed parametric optimization method is much more efficient than the CPLEX solver.     

Coresidence With Elderly Parents: A Comparative Study of Southeast China and Taiwan

Using recent survey data from the Panel Study of Family Dynamics (PSFD) on 1,655 married persons born in 1964-1976 in southeastern China and Taiwan, we studied coresidence with elderly parents using a multinomial probit model for coresidence type and an ordered probit model for residential distance. The study yielded four findings: (a) Patrilocal coresidence was more prevalent in Taiwan than in China; (b) matrilocal coresidence was more prevalent in China; (c) practical factors mattered in both places; (d) in Taiwan only, a couple's economic resources facilitated breaking away from patrilocal coresidence. The findings suggest that, although economic development does not necessarily result in less traditional familial culture, personal economic resources may enable individual couples to deviate from tradition.     

基于稳健Cook距离的时间序列异常值诊断

Cook距离公式常用于回归模型的异常值诊断,但由于公式中的样本方差■对异常值敏感,导致公式缺乏稳健性,使得诊断效果不理想。基于以上问题,文章选取绝对离差中位数作为样本标准差的稳健估计量,得到了样本方差■的稳健估计量,进而构造出稳健Cook距离公式;借鉴传统Cook距离的回归模型异常值诊断理论,将稳健Cook距离公式应用于时间序列异常值诊断,拓展了传统Cook距离公式的异常值诊断领域。通过选取模拟样本量分别为50、100、200,污染率分别为0、1%、5%、10%的ARMA(1,1)序列及金融时间序列进行实例分析,结果发现:(1)在无污染时,稳健Cook距离法与常规Cook距离法的诊断正确率均为100%,两者没有出现"误诊"现象;(2)在样本量、污染率同时增大时,常规Cook距离诊断正确率急剧下降,当污染率达到5%及以上时,已基本无诊断力,而稳健Cook距离法依然能保持较高的诊断力。稳健Cook距离法不仅能应用于时间序列异常值诊断,也能应用于回归分析的异常值诊断。     

IPTV——流媒体技术在农村远程教育中的应用

本文旨在阐述流媒体技术基础,IPTV的结构功能,来实现流媒体及IPTV架构在具体环境中的应用。     

浅析当代男子优秀三级跳远运动员三跳比例

本文以具有当今世界水平男子优秀三级跳远选手的比赛成绩为依据,运用不同时期三级跳远最佳三跳组合的模式,研究了三级跳远成绩与三跳比例的关系,找出了影响不同类型运动员三级跳远比例及成绩的主要优势因素,论述了三级跳远运动员应有不同的中心训练任务和训练方法。